Abstract
Radar technology offers much appeal for contactless vital sign monitoring. While most radar-based approaches achieve reasonable performance for single-person scenarios, they suffer from inaccurate vital sign estimates for multiple individuals, especially when the subjects occupy the same range bin. In addition, complex interferences due to environmental clutter and random body movements (RBMs) further exacerbate the issue of poor performance. We propose a resonance-based sparse separation (RBSS) algorithm for contactless vital sign measurement using millimeter wave (mmWave) multiple-input multiple-output (MIMO) radar. The proposed algorithm utilizes the resonance-based signal decomposition and can achieve reliable reconstruction of cardiopulmonary signals and precise estimates of respiration rate (RR) and heart rate (HR) for multiple individuals located within the same range bin. Experiment results demonstrate the efficacy of the proposed method, even under conditions of heavy clutter and moderate RBMs.
Original language | English |
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Journal | Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing |
DOIs | |
Publication status | Published - 2025 |
Externally published | Yes |
Event | 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 - Hyderabad, India Duration: Apr 6 2025 → Apr 11 2025 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
ASJC Scopus Subject Areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Keywords
- Contactless vital sign monitoring
- millimeter wave (mmWave)
- multiple-input multiple-output (MIMO) radar
- resonance-based sparse separation (RBSS)